SLA Management Best Practices

Eagle recommends the following best practices for creating and using SLAs:

Define your business requirements in an Excel spreadsheet that captures your processing playbook and expectations step by step.
Use this Excel spreadsheet to create matching SLAs and SLA groups.
Set expected values for the SLA conditions and compare those values against the actual system metrics..
Monitor current day operations in Automation Center and run historical SLA reports in System Management Center.
Tune and adjust the SLA condition values based on historical data and future system changes such as new Eagle versions, increased database size, etc.
Add scheduled email notifications to stay on top of SLA performance.

Click the above links to see these recommendations as applied for a sample SLA use case.

Sample SLA Use Case

The following is an example of how SLA best practices can be used to translate your Start of Day (SOD) playbook into SLAs.

Define your business requirements in an Excel spreadsheet that captures your processing playbook and expectations step by step.
In the Start of Day playbook, various daily operations must be tracked and reported on to monitor the successful outcomes of each individual task as well as that of the overall SOD result. In this example, we put together a simple listing of these operations, identifying the task name, description and data source, the operation type (schedule, message stream), its designated measure type (start-time, duration) and the expected benchmark around this operation (duration less than 10 minutes). We then ordered these tasks using logical grouping categories for summary view purposes.
Use this Excel spreadsheet to create matching SLAs and SLA groups.
With these business requirements in place, the next step then calls for creating corresponding SLAs to match the above SOD task list and their grouping order. Using Automation Center's SLA editors, we reflected the entries from the SOD playbook spreadsheet and added SLA and SLA Group definitions using exact settings.
Set expected values for the SLA conditions and compare those values against the actual system metrics.
Setting the expected and correct SLA benchmark may require several iterations to make sure that the values and conditions are properly defined for each SLA. Automation Center's SLA wizard provides simple and easy to use steps for specifying the SLA's data source and measure type (KPIs and KPI Attributes), for calibrating the SLA benchmark by "experimenting" with different value settings and observing the resulting status all within the wizard.
Monitor current day operations in Automation Center and run historical SLA reports in System Management Center.
With the SLA metadata definitions in place, you can immediately start monitoring and comparing the actual metric results vs. the benchmark settings. You can monitor and report on SLA and SLA Group from inside Automation Center or by running the related reports in Systems Management Center.
Tune and adjust the SLA condition values based on historical data and future system changes such as new Eagle versions, increased database size, etc.
The SLA wizard's Validate step allows you to adjust the benchmark values and test these adjustments with or without saving them. You may also want to consult the historical data as you are making these adjustments.